Software defect prediction analysis using machine learning techniques
There is always a desire for defect-free software in order to maintain software quality for
customer satisfaction and to save testing expenses. As a result, we examined various known …
customer satisfaction and to save testing expenses. As a result, we examined various known …
A feature selection model for software defect prediction using binary Rao optimization algorithm
K Thirumoorthy - Applied Soft Computing, 2022 - Elsevier
In this digital world, using software has become an important part of daily life and business.
The software must be rigorously tested in order to avert a financial crisis. The defect-free …
The software must be rigorously tested in order to avert a financial crisis. The defect-free …
Software defect prediction using hybrid techniques: A systematic literature review
R Malhotra, S Chawla, A Sharma - Soft Computing, 2023 - Springer
Software defect prediction is the process of developing predictive models that helps in the
early identification of defect-prone modules based on software metrics and defect data. It …
early identification of defect-prone modules based on software metrics and defect data. It …
[HTML][HTML] Software fault prediction based on change metrics using hybrid algorithms: An empirical study
Quality of the developed software depends on its bug free operation. Although bugs can be
introduced in any phase of the software development life-cycle but their identification in …
introduced in any phase of the software development life-cycle but their identification in …
A clustering approach for software defect prediction using hybrid social mimic optimization algorithm
K Thirumoorthy, JJJ Britto - Computing, 2022 - Springer
In this information era, software usage is intertwined with daily routine work and business.
Defects in software can cause a severe economic crisis. It is a crucial task in the software …
Defects in software can cause a severe economic crisis. It is a crucial task in the software …
[PDF][PDF] Hybrid ensemble learning technique for software defect prediction
MZ Khan - International Journal of Modern Education & Computer …, 2020 - mecs-press.net
The reliability of software depends on its ability to function without error. Unfortunately, errors
can be generated during any phase of software development. In the field of software …
can be generated during any phase of software development. In the field of software …
Comprehensive Survey of different Machine Learning Algorithms used for Software Defect Prediction
V Gururaj, KR Umadi, M Kumar… - … on Decision Aid …, 2022 - ieeexplore.ieee.org
The software development life cycle is a long and complicated process. It consists of
analysis, design, development, testing and deployment. Defect prediction is the technique of …
analysis, design, development, testing and deployment. Defect prediction is the technique of …
An Ensemble Model for Software Defect Prediction
Software testing is one of the important ways to ensure the quality of software. It is found that
testing cost more than 50% of overall project cost. Effective and efficient software testing …
testing cost more than 50% of overall project cost. Effective and efficient software testing …
Predicting Software Defects in Hybrid MPI and OpenMP Parallel Programs Using Machine Learning
AS Althiban, HM Alharbi, LA Al Khuzayem, FE Eassa - Electronics, 2023 - mdpi.com
High-performance computing (HPC) and its supercomputers are essential for solving the
most difficult issues in many scientific computing domains. The proliferation of computational …
most difficult issues in many scientific computing domains. The proliferation of computational …
A novel multiple ensemble learning models based on different datasets for software defect prediction
Software testing is one of the important ways to ensure the quality of software. It is found that
testing cost more than 50% of overall project cost. Effective and efficient software testing …
testing cost more than 50% of overall project cost. Effective and efficient software testing …